Valuing pharmacogenetic testing services: A comparison of patients' and health care professionals' preferences

Value in Health

Volumn 14, Issue 1, 2011, Pages 121-134

  Payne, Katherine ^a   Fargher, Emily A ^b   Roberts, Stephen A ^a   Tricker, Karen ^a   Elliott, Rachel A ^c   Ratcliffe, Julie ^d   Newman, William G ^a,e  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

^b BANGOR UNIVERSITY   (United Kingdom)

^c UNIVERSITY OF NOTTINGHAM   (United Kingdom)

^d UNIVERSITY OF ADELAIDE   (Australia)

^e Manchester Biomedical Research Centre   (United Kingdom)

Author keywords

Discrete choice experiment; Health care professional; Patient's preferences

Indexed keywords

AZATHIOPRINE; IMMUNOSUPPRESSIVE AGENT;

ACCURACY; ARTICLE; CLINICAL PRACTICE; DNA DETERMINATION; GENETIC SCREENING; HEALTH CARE PERSONNEL; HUMAN; INFORMATION; MAJOR CLINICAL STUDY; PATIENT PREFERENCE; PHARMACOGENETICS; PREDICTION; PRIORITY JOURNAL; RISK FACTOR; SAMPLE SIZE; TURNAROUND TIME; ADOLESCENT; ADULT; AGED; COMPARATIVE STUDY; FEMALE; GENETIC SERVICE; GENETICS; HEALTH CARE SURVEY; HEALTH PERSONNEL ATTITUDE; MALE; MIDDLE AGED; NEUTROPENIA; PATIENT EDUCATION; REGRESSION ANALYSIS; UNITED KINGDOM;

ADOLESCENT; ADULT; AGED; AGED, 80 AND OVER; ATTITUDE OF HEALTH PERSONNEL; AZATHIOPRINE; FEMALE; GENETIC SERVICES; GREAT BRITAIN; HEALTH CARE SURVEYS; HUMANS; IMMUNOSUPPRESSIVE AGENTS; MALE; MIDDLE AGED; NEUTROPENIA; PATIENT EDUCATION AS TOPIC; PATIENT PREFERENCE; PHARMACOGENETICS; REGRESSION ANALYSIS;

EID: 79952656828     PISSN: 10983015     EISSN: 15244733     Source Type: Journal    
DOI: 10.1016/j.jval.2010.10.007     Document Type: Article

References (51)

1. The Royal Society. Pharmacogenetics: the hopes and realities of personalised medicines. A guide for health professionals. London, England: The Royal Society, September 2005.
2. Flockhart DA, Skaar T, Berlin DS, et al. Clinically available pharmacognomics tests. Clin Pharmacol Ther 2009;86:109-13.
3. Marsh S. Impact of pharmacogenomics on clinical practice in oncology. Molecular Diag & Therapy 2007;11:79-82. (Pubitemid 46572568)
4. *5701 screening for hypersensitivity to abacavir. NEJM 2008;358:568-79.
5. Fargher EA, Tricker K, Newman B, et al. Current use of pharmacogenetic testing: a national survey of thiopurine methyltransferase (TPMT) testing prior to azathioprine prescription. J Clin Pharm Ther 2007;32:187-95. (Pubitemid 46449703)
6. Anon. Carbamazepine: genetic testing recommended in some Asian populations. Drug Safety Update 2008;1:5.
7. Vegter S, Boersma C, Rozenbaum M, et al. Pharmacoeconomic evaluations of pharmacogenetic and genomic screening programmes: a systematic review on content and adherence to guidelines. Pharmacoeconomics 2008;26:569-87. (Pubitemid 351871553)
8. Shah J. Criteria influencing the clinical uptake of pharmacogenomic strategies. BMJ 2004;328:1482-6. (Pubitemid 38829912)
9. Greenhalgh T, Robert G, Macfarlane F et al. Diffusion of innovations in service organisations: systematic review and recommendations. Milbank Q 2004;82:581-629. (Pubitemid 40143100)
10. Sanderson J, Ansari A, Marinaki T, Duley J. Thiopurine methyltransferase: should it be measured before commencing thiopurine drug therapy? Ann Clin Biochem 2004;41:294-302. (Pubitemid 38954878)
11. Teml A, Schaeffeler E, Herrlinger KR, et al. Thiopurine treatment in inflammatory bowel disease: clinical pharmacology and implication of pharmacogenetically guided dosing. Clin Pharmacokinet 2007;46:187-208. (Pubitemid 46425646)
12. Coulthard S, Hogarth L. The thiopurines: an update. Invest New Drugs 2005;23:523-32. (Pubitemid 43162471)
13. Dubinsky MC. Azathioprine, 6-mercaptopurine in inflammatory bowel disease: pharmacology, efficacy, and safety. Clin Gastroenterol Hepatol 2004;2:731-43. (Pubitemid 39200711)
14. Timmer A, McDonald JW, Macdonald JK. Azathioprine and 6-mercaptopurine for maintenance of remission in ulcerative colitis. Cochrane Database Syst Rev 2007: CD000478.
15. Payne K, Newman W, Fargher EA, et al. TPMT testing in rheumatology: any better than routine monitoring? Rheumatology 2007;46:727-9. (Pubitemid 47061698)
16. Anstey AV, Wakelin S, Reynolds NJ; British Association of Dermatologists Therapy, Guidelines and Audit Subcommittee. Guidelines for prescribing azathioprine in dermatology. Br J Dermatology 2004;151:1123.
17. Chakravarty K, McDonald H, Pullar T, et al. BSR & BHPR guideline for disease-modifying anti-rheumatic drug therapy in consultation with the British Association of Dermatologists. Rheumatology (Oxford). 2008;47:924-5.
18. Gurwitz D, Rodríguez-Antona C, Payne K, et al. Improving pharmacovigilance in Europe: TPMT genotyping and phenotyping in the UK and Spain. Eur J Hum Genet. 2009;17:991-8; doi:10.1038/ejhg.2009.10.
19. Fargher EA, Tricker K, Newman B, et al. Current use of pharmacogenetic testing: a national survey of thiopurine methyltransferase (TPMT) testing prior to azathioprine prescription. J Clin Pharm Ther 2007;32:187-95. (Pubitemid 46449703)
20. Meggitt SJ, Gray JC, Reynolds NJ. Azathioprine dosed by thiopurine methyltransferase activity for moderate-tosevere atopic eczema: a double-blind, randomised controlled trial. Lancet 2006;367:839-46. (Pubitemid 43363371)
21. Newman W, Payne K, Tricker K, et al. A pragmatic randomised controlled trial of thiopurine methyltransferase (TPMT) genotyping in the management of patients, prior to azathioprine treatment: the TARGET study (under peer review).
22. Grosse SD, Khoury MJ. What is the clinical utility of genetic testing? Genet Med 2006;8:448-50. (Pubitemid 44289007)
23. Payne K, Newman WG, Gurwitz D, et al. TPMT testing in azathioprine: a "cost-effective use of healthcare resources"? Per Med 2009;6:103-13.
24. Newman W, Payne K. Removing barriers to a clinical pharmacogenetics service. Per Med 2008;5:471-80.
25. Newton R, Lithgow J, Li Wan Po A, et al. How will pharmacogenetics impact on pharmacy practice? Pharmacists' views and educational priorities. National Genetics Education and Development Centre and The Royal Pharmaceutical Society of Great Britain. November 2007.
26. Fargher EA, Eddy C, Newman W, et al. Patients' and healthcare professionals' views on pharmacogenetic testing and its future delivery in the NHS. Pharmacogenomics 2007;8:1511-9. (Pubitemid 350286396)
27. Ryan M, Farrar S. Using conjoint analysis to elicit preferences for health care. BMJ 2000;320:1530-3. (Pubitemid 30330316)
28. Ryan M, Gerard K. Using discrete choice experiments to value health care programmes: current practice and future research reflections. Appl Health Econ Health Policy 2003;2:55-64.
29. Ratcliffe J, Longworth L. Investigating the structural reliability of a discrete choice experiment within health technology assessment. Int J Tech Assess Health Care 2002;18:139-44. (Pubitemid 34408536)
30. Sloan N J A. A library of orthogonal arrays. Available from: http://www.research.att.com/~njas/oadir/index.html [Accessed February 8, 2010].
31. Street D, Burgess L. The Construction of Optimal Stated Choice Experiments: Theory and Methods. London: Wiley, 2007.
32. Burgess L. (2007) Discrete Choice Experiments [computer software]. Department of Mathematical Sciences, University of Technology, Sydney. Available from: http://crsu.science.uts.edu.au/choice/[Accessed November 3, 2010].
33. San Miguel F, Ryan M, Amaya-Amaya M. "Irrational" stated preferences: a quantitative and qualitative investigation. Health Econ 2005;14:307-22. (Pubitemid 40360765)
34. Lancaster K. A new approach to consumer theory. J Polit Econ 1966;74:132-57.
35. Scott A. Identifying and analysing dominant preferences in discrete choice experiments: an application in health care. J Econ Psychol 2002;23:383-98.
36. Lancaster K. Operationally relevant characteristics in the Theory of consumer behavior. In: Peston M, Corry B (eds.). Essays in Honor of Lord Robbins. London: MacMillan, 1972.
37. Lanscar E, Louviere J. Conducting discrete choice experiments to inform healthcare decision making. A user's guide. Pharmacoeconomics 2008;26:661-77. (Pubitemid 351989058)
38. Swait J, Louviere J. The role of the scale parameter in the estimation and comparison of multinomial Logit models. J Mark Res 1993;30:305-14.
39. Bech M, Gyrd-Hansen D. Effects coding in discrete choice experiments. Health Econ 2005;14:1079-83. (Pubitemid 41419196)
40. Higashi MK, Veenstra DL, Kondo LM, et al. Association between CYP2C9 genetic variants and anticoagulationrelated outcomes during warfarin therapy. JAMA 2002;287:1690-8. (Pubitemid 34289221)
41. Herbild L, Bech M, Gyrd-Hansen D. Estimating the Danish populations' preferences for pharmacogenetic testing using a discrete choice experiment. The case of treating depression. Value Health 2009;12:560-7.
42. Department of Health. Our health, our care, our say. London: Department of Health, 2006.
43. Darzi A. High quality care for all. London: Department of Health, 2008.
44. Ratcliffe J, Buxton M. Patient's preferences regarding the process and outcomes of high technology medicine: an application of conjoint analysis to liver transplantation. Int J Technol Assess Health Care 1999:15: 340-51. (Pubitemid 29380444)
45. Longworth L, Ratcliffe J, Boulton M. Investigating women's preferences for maternity care during the intrapartum stage. Health Soc Care Community 2001:9;404-13. (Pubitemid 33696686)
46. Clemerson JP, Payne K, Bissell P, Anderson C. Pharmacogenetics - the next challenge for pharmacy? Pharm World Sci 2006;18:126-31.
47. Gurwitz D, Lunshof JE, Dedoussis G, et al. Pharmacogenomics education: International Society of Pharmacogenomics recommendations for medical, pharmaceutical, and health schools deans of education. Pharmacogenomics J 2005;5:221-5. (Pubitemid 41131714)
48. Hole A. Modelling heterogeneity in patients' preferences for the attributes of a general practitioner appointment. J Health Econ 2008;27:1078-94.
49. Bartels R, Fiebig DG, van Soest A. Consumers and experts: an economitric analysis of the demand for water heaters. Empir Econ 2006;31:369-91.
50. Fiebig DG, Keane MP, Louviere J, Wasi N. The generalized multinomial logit model: accounting for scale and coefficient heterogeneity. Marketing Science 2010;29:393-421.
51. Louviere J, Street D, Burgess L, et al. Modelling the choices of individual decision-makers by combing efficient choice experiment designs with extra preference information. J Choice Modelling 2009;1:128-63.